I am currently an Assistant Professor (tenure-track) at the College of Information Sciences and Technology, Penn State University, where I co-direct the Applied Cognitive Science Lab. I have been a research psychologist in the Department of Psychology at Carnegie Mellon University and hold a PhD in Cognitive Science in 2008 from the University of Edinburgh (School of Informatics). I have held a number of positions in research, R&D (industry), and I have substantial experience in natural language processing technology and software development. I run the Aquamacs project that has more than 13,000 users world-wide. Before my research career, I worked as a radio journalist in the German ARD network. I am a private pilot and fly my own sailplane for fun, and have been active in the management of some great gliding clubs.
What's the "Stuff of Thought"? How do humans make decisions, and how do they make mistakes? How do we produce language? Can thinking, remembering, communicating individuals form a big, thinking organism?
These are the questions that drive my academic interests, which span computer science, linguistics and cognitive science.
To find answers, I employ data-driven computational methods. Based on empirical data, I build models of cognitive processes and small- and large-scale cognitive simulations. The goal is to predicively model learning and adaptation in human subjects, specifically during interaction within pairs and larger groups.
Cognitive modeling and network simulation techniques have allowed a recent growth in interest for the interaction of cognitive mechanisms with the social environment. Individuals adapt their linguistic expressions quickly to their interaction partners, and new communicative conventions may soon spread through a network of connected agents. Cognitive modeling frameworks such as ACT-R, validated and refined through careful experimentation, as well as computational tools now allow the larger-scale simulation of human societies and the uptake of existing language resources (corpora) in the quest for the architecture of the human language faculty. Networked experimentation platforms facilitate large-scale data-collection. Datasets collected in real-life situations let us test cognitive and psycholinguistic models. Once validated, they will make better predictions and cover broad ranges of human behavior. This combination of broad coverage and large-scale simulation requires new computational tools, new methodologies, new datasets and new experimental designs.
Contact: David Reitter, Penn State University. E-mail or